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Donors

Donors are individuals who contribute resources, such as money, time, or materials, to support a cause or organization.
They play a crucial role in enabling research, healthcare, and other important initiatives to thrive.
PubCompare.ai can help researchers identify the most effective protocols and products for their work by comparing relevant donor information from literature, preprints, and patents.
By streamlining the research workflow and maximiizing impact, PubCompare.ai empowers researchers to make the best use of donor contributions and drive meaningful progress in their fields.

Most cited protocols related to «Donors»

1
Comprehensive Transcript Alignment Analysis
Cited 473 times
Reconstructed transcripts were mapped to genome sequences using GMAP, reporting only the single top scoring alignment per sequence. Individual introns and complete splicing patterns were extracted from each of the alignments and compared to reference annotations using custom PERL scripts. Unique introns (missing from the reference annotations) were required to contain consensus dinucleotide splice sites (GT or GC donors and AG acceptors).
Grabherr M.G., Haas B.J., Yassour M., Levin J.Z., Thompson D.A., Amit I., Adiconis X., Fan L., Raychowdhury R., Zeng Q., Chen Z., Mauceli E., Hacohen N., Gnirke A., Rhind N., di Palma F., Birren B.W., Nusbaum C., Lindblad-Toh K., Friedman N, & Regev A. (2011). Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nature biotechnology, 29(7), 644-652.
Publication 2011
Dinucleoside Phosphates Donors Introns Sequence Alignment
2
Comprehensive Transcript Alignment Analysis
Cited 448 times
Reconstructed transcripts were mapped to genome sequences using GMAP, reporting only the single top scoring alignment per sequence. Individual introns and complete splicing patterns were extracted from each of the alignments and compared to reference annotations using custom PERL scripts. Unique introns (missing from the reference annotations) were required to contain consensus dinucleotide splice sites (GT or GC donors and AG acceptors).
Grabherr M.G., Haas B.J., Yassour M., Levin J.Z., Thompson D.A., Amit I., Adiconis X., Fan L., Raychowdhury R., Zeng Q., Chen Z., Mauceli E., Hacohen N., Gnirke A., Rhind N., di Palma F., Birren B.W., Nusbaum C., Lindblad-Toh K., Friedman N, & Regev A. (2011). Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nature biotechnology, 29(7), 644-652.
Publication 2011
Dinucleoside Phosphates Donors Introns Sequence Alignment
3
Epigenetic Profiling of Colorectal Cancer Cohort
Cited 253 times
We profiled the epigenetic landscape of 990 unique donors forming the control cohort of the Assessment of Risk for Colorectal Cancer Tumours in Canada (ARCTIC) project.14 (link) Fifteen μl of lymphocyte-derived DNA extracted (at an average concentration 90 ng/μl) was bisulfite-converted using the EZ-96 DNA Methylation-Gold Kit (Zymo Research, Orange, CA); 4μl of bisulfite-treated DNA was then analyzed on the HumanMethylation450 BeadChip from Illumina according to the manufacturer’s protocol. Intensities were normalized using Illumina’s internal normalization probes and algorithms, without background subtraction. Beta values with assigned detection p-values > 0.01 were treated as missing data. CpG sites with more than 1% missing data across all samples were discarded.
We removed from analysis samples that were outliers with respect to any one of the internal control probes (excluding probes designed to evaluate the background noise and probes designed to normalize the data) and samples that were not of non-Hispanic white ancestry, either self-declared or by investigation of genetic ancestry using genome-wide SNP data. After sample exclusion, we were left with 489 adult males and 357 adult females.
Chen Y.A., Lemire M., Choufani S., Butcher D.T., Grafodatskaya D., Zanke B.W., Gallinger S., Hudson T.J, & Weksberg R. (2013). Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics, 8(2), 203-209.
Publication 2013
Adult Colorectal Carcinoma Colorectal Neoplasms DNA Methylation Donors Genome Gold Health Risk Assessment Hispanics hydrogen sulfite Lymphocyte Males Malignant Neoplasms Neoplasms Reproduction Woman
4
Visualizing Ligand Binding Site Properties
Cited 216 times
Autodock uses interaction maps for docking. Prior to the actual docking run these maps are calculated by the program autogrid. For each ligand atom type, the interaction energy between the ligand atom and the receptor is calculated for the entire binding site which is discretized through a grid. This has the advantage that interaction energies do not have to be calculated at each step of the docking process but only looked up in the respective grid map. In addition to speeding up a docking runs the grid maps on their own can also provide value hints for ligand optimization. Since a grid map represents the interaction energy as a function of the coordinates their visual inspection may reveal potential unsaturated hydrogen acceptors or donors or unfavourable overlaps between the ligand and the receptor. The plugin therefore provides the functionality to visualize these grid maps in PyMOL. The maps generated by autogrid are converted to a file format readable by PyMOL (DX format) which allows to draw isosurfaces and isomeshes analogous to electron density maps. Since several maps can be loaded and controlled simultaneously, a rapid inspection of several interaction types is made very easily. Figure 3 shows how these grid maps can be controlled via the plugin.

Autodock grid maps displayed with different contour levels. a Map for interactions of aliphatic carbon atoms at contour level 5 kcal/mol. b Same map at contour level −0.3 kcal/mol. c Hydrogen bond donor map at contour level −0.5 kcal/mol

In Fig. 3A an isosurface at a contour level of 5 kcal/mol for the interaction of the protein with aliphatic carbon atoms is shown. Such a setting may be used to get a visual impression of the overall shape of the binding site. Ligand modifications which cause a penetration of such a wall will most likely not enhance the affinity. In Fig. 3B the same map is visualized at a contour level of −0.3 kcal/mol. As can be seen, the shape of the surface, here shown as isomesh, roughly describes an envelope of the ligand and reveals putative spots of attractive interactions that may guide further ligand optimization. Likewise, hydrogen bond donor or acceptor interaction maps can guide ligand optimization since they might reveal unsaturated acceptor or donor positions (Fig. 3C).
The plugin provides functionality to handle different interaction maps and representations at different contour levels at the same time and hence, offers the possibility to visualize different binding site properties which may provide valuable insights for structure-based drug design.
Seeliger D, & de Groot B.L. (2010). Ligand docking and binding site analysis with PyMOL and Autodock/Vina. Journal of Computer-Aided Molecular Design, 24(5), 417-422.
Publication 2010
Binding Sites Carbon Donors Electrons Exanthema Hydrogen Hydrogen Bonds Ligands Microtubule-Associated Proteins Nuclear Energy Proteins Tissue Donors Vision
5
Comprehensive Preprocessing of Sequencing Datasets
Cited 210 times
Full details of each dataset9 (link),10 (link),17 (link),20 ,21 (link),37 (link),42 ,50 (link),55 ,64 (link)–69 (link), including data type, sample type, source, and normalization approach, are available in Supplementary Table 1. Briefly, next generation sequencing datasets were downloaded and analyzed using the authors’ normalization settings unless otherwise specified; these consisted of transcripts per million (TPM), reads per kilobase of transcript per million (RPKM), or fragments per kilobase of transcript per million (FPKM) space. For analyses in log2 space, we added 1 to expression values prior to log2 adjustment. Affymetrix microarray datasets were summarized and normalized as described in ‘Gene expression profiling – Microarrays’ (Supplementary Note 1), using RMA in cases where bulk tissues and ground truth cell subsets were profiled on the same Affymetrix platform, and otherwise using MAS5 normalization. NanoString nCounter data were downloaded from the supplement of Chen et al.20 and analyzed with batch correction in non-log linear space, but without any additional preprocessing.
Two publicly available PBMC datasets from healthy donors profiled by Chromium v2 (5’ and 3’ kits) were downloaded (Supplementary Table 1) and preprocessed as described in ‘Gene expression profiling – Single-cell RNA-seq’ (Supplementary Note 1), with the following minor modifications. During quality control, we excluded cells with >5000 expressed genes for 5’ PBMCs, >4000 expressed genes for 3’ PBMCs, and <200 expressed genes for both datasets. Seurat “FindClusters” was applied on the first 20 principal components, with the resolution parameter set to 0.6. Cell labels were assigned as described above. In addition, myeloid cells were defined by high CD68 expression, megakaryocytes by high PPBP expression, and dendritic cells by high FCER1A expression.
For the 3’ FL signature matrix in Supplementary Figs. 11d, and14a-b, publicly available 10x Chromium v2 scRNA-seq data (3’ kit)70 were downloaded (Supplementary Table 1) and preprocessed as described for the 10x PBMC signature matrices above, but with the following differences. Seurat “FindClusters” was applied on the first 10 principal components, with the resolution parameter set to 0.6. Cell labels were assigned based on the following canonical marker genes (MS4A1 = B cells; CD3E, CD8A and CD8B = CD8 T cells; CD3E and CD4 = CD4 T cells).
Newman A.M., Steen C.B., Liu C.L., Gentles A.J., Chaudhuri A.A., Scherer F., Khodadoust M.S., Esfahani M.S., Luca B.A., Steiner D., Diehn M, & Alizadeh A.A. (2019). Determining cell-type abundance and expression from bulk tissues with digital cytometry. Nature biotechnology, 37(7), 773-782.
Publication 2019
B-Lymphocytes CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes Cells Chromium Dendritic Cells Dietary Fiber Dietary Supplements Donors Figs Genes Megakaryocytes Microarray Analysis Myeloid Cells platelet basic protein, human RNA-Seq Single-Cell RNA-Seq Tissues

Most recents protocols related to «Donors»

1
Skin Flux Assay with Human Epidermis
Not available on PMC !

Example 2

(Test 4) A skin flux assay was performed using a vertical Franz diffusion cell having a diffusion area of 0.64 cm2 and a volume of 7.5 mL. The assay was conducted at 32° C. with continuous stirring. Heat-separated human cadaver epidermis was used in the assay, the epidermis being stored at −20° C. after the heat stripping procedure. The human epidermis was thawed prior to being mounted on the diffusion cell. A test compound was applied on the skin, and the diffusion cell was closed by screw-cap. At various time intervals, whole medium or receptor medium was replaced by fresh medium. Part of the collected medium was used to calculate the skin flux of the test compound. The skin flux of various test compounds was evaluated using human epidermis from different donors. N=4 replicates were performed for each test compound tested on human epidermis from a particular donor.

Results of the skin flux assay are shown in Table 1 above. For Table 1, the code for the average skin flux of the test compounds tested on human epidermis from a particular donor is:

+=low to moderate skin flux

++=medium skin flux

+++=high skin flux

++++=very high skin flux

US11866402B2. Treprostinil derivatives and compositions and uses thereof (2024-01-09). CORSAIR PHARMA, INC. [US]. Inventors: Xiaoming Zhang [US], Meenakshi S. Venkatraman [US], Cyrus K. Becker [US].
Full text: Click here
Patent 2024
Biological Assay Cadaver Cells derivatives Diffusion Donors Epidermis Homo sapiens Skin Test, Skin Tissue Donors treprostinil
2
Enhancing CRISPR-mediated HDR Efficiency
Not available on PMC !

Example 7

A mouse model was used to test HDR efficiency of the modified DNA donor molecules in vivo. A 4.6 kb long traffic light reporter (TLR), was integrated, or knocked-in, into the ROSA-26 locus. HDR efficiency was determined using donors either as plasmid or end-modified double-stranded PCR products. Using donors with 2′-OMe-RNA-TEG 5′ end-modifications, it was found that 9 out of 15 (60%) founder animals had the insert compared to 1/11 (9%) using plasmid as a donor. This result indicates that end-modifications make the donor molecules more potent even in mammalian (in vivo) settings (FIG. 23). The injection mixtures for this experiment are as follows: plasmid donor experiment—Cas9 mRNA (50.0 ng/μl), Cas9 protein (50.0 ng/μl), sgRNA (20 ng/μl), plasmid DNA donor (10 ng/μl); end-modified donor experiment—Cas9 mRNA (50.0 ng/μl), Cas9 protein (50.0 ng/μl), sgRNA (20 ng/μl), modified DNA donor (1 ng/μl).

US11873487B2. Compositions and methods for improved gene editing (2024-01-16). UNIVERSITY OF MASSACHUSETTS [US]. Inventors: Craig Mello [US], Krishna Sumanth Ghanta [US].
Full text: Click here
Patent 2024
Animals CRISPR-Associated Protein 9 Donors Light Mammals Mus Plasmids RNA, Messenger Rosa Tissue Donors
3
Enhancing HDR Efficiency with Modified DNA Donors
Not available on PMC !

Example 9

Modified DNA donors with a 5′ spermine modification were tested for their effect on HDR efficiency. Using the HE293 TLR assay, it was found that these spermine-modified DNA donors were more effective than unmodified DNA donors. The improvement in efficiency is comparable to that of TEG alone as well. When combining TEG and spermine modifications in the same DNA donor, there was also an increase in the HDR efficiency compared to the unmodified donors (FIG. 26).

These combined results indicate that 2′-OMe RNA, PEG, spermine, and combinations of these modifications make DNA donor molecules more potent for HDR.

US11873487B2. Compositions and methods for improved gene editing (2024-01-16). UNIVERSITY OF MASSACHUSETTS [US]. Inventors: Craig Mello [US], Krishna Sumanth Ghanta [US].
Full text: Click here
Patent 2024
Biological Assay DNA Donors Spermine Tissue Donors
4
MetCAR T Cells Transduction and Characterization
Not available on PMC !

Example 3

To produce MetCAR T cells, peripheral blood mononuclear cells (PBMCs) isolated from healthy donors were stimulated with anti-CD3/CD28 antibodies in the presence of IL-7 (10 ng/ml) and IL-15 (5 ng/ml) for 24 hr to expand CD3+ T cells for transduction with MetCARs. CD3+ T cells are regularly tested to reach >90% after stimulation (data not shown). Because all MetCAR constructs use CD19 as a tag, the expression of CD19 by flow cytometer is used as the transduction efficacy (FIGS. 2A, 2B). With NT cells as a negative control, MetCAR transduction efficiency ranged from 60-90% with no significant differences between MetCAR constructs (FIGS. 2A, 2B). MetCAR expression levels were determined using CD3ζ as a marker (FIG. 2C). Results showed that both MetCAR.CD28.ζ. and MetCAR.4-1BB.ζ.-transduced T cells had CD3ζ overexpression comparing with non-transduced or CAR.Δ-transduced T cells. p-CD3ζ expression was also observed in MetCAR.CD28.ζ- and MetCAR.4-1BB.ζ.-transduced T cells (FIG. 2C), indicating the activation of TCR in MetCAR-T cells.

US11866493B2. Single-chain variable fragment of Met monoclonal antibody and methods of use in CAR T cell therapy (2024-01-09). East Tennessee State University Research Foundation [US]. Inventors: Qian Xie [US].
Full text: Click here
Patent 2024
Anti-Antibodies Cells Donors Interleukin-15 PBMC Peripheral Blood Mononuclear Cells T-Lymphocyte
5
Selective Cytotoxicity of Stem Cell-Derived Neutrophils
Not available on PMC !

Example 18

Demonstrating the Selectivity of Stem Cell Derived Neutrophils CKA for Cancer Cells

Neutrophils derived from CD34+ stem cells of three different donors were tested for CKA against both HeLa cells (cervical cancer), PANC-1 cells (pancreatic cancer) as well as non-cancer MCF-12F cells (normal breast epithelial cells).

FIG. 9 shows the maximum percentage cytotoxicity recorded by the CKA assay (xCELLigence assay—carried out for up to 45 hours) against each cancer cell type and non-cancer cell type for donors LC267, LC268 and LC269. Advantageously, SCDNs were highly selective for cancer cells showing minimal impact on non-cancer cells. Similarly to FIG. 3 showing DDN from the same donors, SCDNs from donor LC269 had the highest CKA with LC268 second, and LC267 showing the lowest CKA. Thus, it can be concluded that CKA is a genetically-defined rather than epigenetically-defined trait.

Similar results were obtained for SCDNs of donors LC252, LC253 and LC254 (FIG. 10).

US11878033B2. Cancer-killing cells (2024-01-23). LIFT BIOSCIENCES LTD [GB]. Inventors: Alex Blyth [GB], Nico Bruyniks [GB].
Full text: Click here
Patent 2024
Biological Assay Breast Cells Cervical Cancer Cytotoxin Donors Epithelial Cells HeLa Cells Malignant Neoplasms Neutrophil Pancreatic Cancer Stem, Plant Stem Cells Tissue Donors

Top products related to «Donors»

1
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
2
Penicillin streptomycin by Thermo Fisher Scientific
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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
3
Ficoll paque plus by GE Healthcare
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Ficoll-Paque PLUS is a sterile, ready-to-use medium for the isolation of mononuclear cells from blood or bone marrow by density gradient centrifugation. It is a polysucrose and sodium diatrizoate solution with a density of 1.077 g/mL.
4
Penicillin by Thermo Fisher Scientific
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Penicillin is a type of antibiotic used in laboratory settings. It is a broad-spectrum antimicrobial agent effective against a variety of bacteria. Penicillin functions by disrupting the bacterial cell wall, leading to cell death.
5
Streptomycin by Thermo Fisher Scientific
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Streptomycin is a broad-spectrum antibiotic used in laboratory settings. It functions as a protein synthesis inhibitor, targeting the 30S subunit of bacterial ribosomes, which plays a crucial role in the translation of genetic information into proteins. Streptomycin is commonly used in microbiological research and applications that require selective inhibition of bacterial growth.
6
Rpmi 1640 by Thermo Fisher Scientific
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RPMI 1640 is a common cell culture medium used for the in vitro cultivation of a variety of cells, including human and animal cells. It provides a balanced salt solution and a source of essential nutrients and growth factors to support cell growth and proliferation.
7
L glutamine by Thermo Fisher Scientific
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L-glutamine is an amino acid that is commonly used as a dietary supplement and in cell culture media. It serves as a source of nitrogen and supports cellular growth and metabolism.
8
Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
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DMEM (Dulbecco's Modified Eagle's Medium) is a cell culture medium formulated to support the growth and maintenance of a variety of cell types, including mammalian cells. It provides essential nutrients, amino acids, vitamins, and other components necessary for cell proliferation and survival in an in vitro environment.
9
Rpmi 1640 medium by Thermo Fisher Scientific
Sourced in United States, China, Germany, United Kingdom, Japan, France, Canada, Australia, Italy, Switzerland, Belgium, New Zealand, Spain, Israel, Sweden, Denmark, Macao, Brazil, Ireland, India, Austria, Netherlands, Holy See (Vatican City State), Poland, Norway, Cameroon, Hong Kong, Morocco, Singapore, Thailand, Argentina, Taiwan, Province of China, Palestine, State of, Finland, Colombia, United Arab Emirates
RPMI 1640 medium is a commonly used cell culture medium developed at Roswell Park Memorial Institute. It is a balanced salt solution that provides essential nutrients, vitamins, and amino acids to support the growth and maintenance of a variety of cell types in vitro.
10
Ficoll paque by GE Healthcare
Sourced in Sweden, United States, United Kingdom, Germany, Canada, Belgium, Italy, Australia, Austria, France, Japan, Singapore, Denmark
Ficoll-Paque is a density gradient medium used for the isolation and purification of cells, such as mononuclear cells, from whole blood or other biological samples. It is designed to separate different cell types based on their density differences during centrifugation.

More about "Donors"

Donors are the unsung heroes of research, healthcare, and other vital initiatives.
These individuals contribute invaluable resources, such as money, time, and materials, to support important causes and organizations.
Their generosity and dedication enable groundbreaking work to thrive.
Effective donor management is crucial for maximizing the impact of research projects.
PubCompare.ai, the leading AI platform for optimizing research protocols, can help researchers identify the most efficient and successful protocols by comparing relevant donor information from literature, preprints, and patents.
This streamlined approach empowers researchers to make the best use of donor contributions and drive meaningful progress in their fields.
Donor contributions can take many forms, from financial donations to the provision of essential materials like Ficoll-Paque PLUS, a widely used density gradient medium for cell separation.
Penicillin, Streptomycin, and other antibiotics are also critical supplies that are often donated to support important research initiatives.
RPMI 1640 medium, DMEM, and L-glutamine are just a few examples of the myriad of resources that donors may provide to enable cutting-edge studies.
By leveraging the insights gleaned from PubCompare.ai's AI-driven comparisons, researchers can identify the most effective protocols and products for their work, ultimately maximizing the impact of donor contributions.
This empowers researchers to streamline their workflows, save time and resources, and make significant advancements in their respective fields.
Donors are the unsung heroes whose generosity and commitment are the bedrock of progress in research, healthcare, and beyond.
PubCompare.ai is proud to support researchers in making the most of these invaluable contributions and driving meaningful change for the betterment of society.